From competency to conscientization: a Freirean critical AI literacy framework for post-secondary education

The rapid growth of artificial intelligence (AI) literacy frameworks in post-secondary education has generated a substantial body of competency-based scholarship focused on technical understanding, applied use, evaluation of AI outputs, and ethical awareness. These contributions are necessary, yet competency specification can leave under-theorized the pedagogical process through which learners move from critical evaluation toward conscientization and transformative action. To that extent, competency-oriented AI literacy risks functioning as a domesticating rather than a liberating educational practice. Drawing on Paulo Freire's theory of conscientization, generative themes, problem-posing education, and praxis, this conceptual paper proposes the Freirean Critical AI Literacy (FCAIL) framework. The paper makes three contributions. Theoretically, FCAIL derives its architecture from specific Freirean educational concepts rather than using Freirean vocabulary to support conclusions reached by other means. Architecturally, FCAIL organizes AI literacy around four interrelated dimensions, each pairing a learner capacity with the educational conditions that enable or constrain it: AI World-Reading, the capacity to read AI as socially and historically produced; Contradiction Naming, the capacity to articulate lived AI-mediated tensions as objects of structural inquiry; Critical Praxis, the capacity to connect critical analysis with action; and Solidary Conscientization, the capacity for shared analysis and collective claim-making. Integratively, FCAIL places Freirean critical pedagogy and decolonial AI scholarship in structural relationship: Freirean theory specifies educational conditions for developing critical consciousness, while decolonial AI scholarship identifies the epistemological stakes for marginalized communities. The decolonial dimension is constitutive across the framework because critical AI literacy remains theoretically incomplete if it does not engage the colonial knowledge hierarchies embedded in AI systems. The paper develops implications for pedagogy, curriculum design, assessment, and institutional governance, positions FCAIL as a complement to competency frameworks, and identifies priorities for empirical research.